Instructions to use monsterapi/CodeAlpaca_LLAMA2_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use monsterapi/CodeAlpaca_LLAMA2_7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "monsterapi/CodeAlpaca_LLAMA2_7B") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from monsterapi/CodeAlpaca_LLAMA2_7B: direct link, hf CLI and curl.
- Browser
- Download file 33.6 MB
-
https://huggingface.co/monsterapi/CodeAlpaca_LLAMA2_7B/resolve/main/adapter_model.bin
- Command line
-
hf download hf://monsterapi/CodeAlpaca_LLAMA2_7B/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/monsterapi/CodeAlpaca_LLAMA2_7B/resolve/main/adapter_model.bin
33.6 MB
- Xet hash:
- 54f0c83558067279497e17d331c867be100672ebcbd214edfd66a6a765c24a6d
- Size of remote file:
- 33.6 MB
- SHA256:
- fb3079c29e8111eae0898444aa78ecdc58a1679a6af2d290201f77fd7699d8d4
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